There's an app for that: content analysis of paid health and fitness apps.
There's an app for that: content analysis of paid health and fitness apps.
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DOI：
10.2196/jmir.1977
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发表时间：
2012-05-14
影响因子：
7.4
通讯作者：
Barrett J
中科院分区：
文献类型：
--
作者：
West JH;Hall PC;Hanson CL;Barnes MD;Giraud-Carrier C;Barrett J
苹果iPhone的推出为开发人员提供了设计第三方应用程序的平台，极大地扩展了移动设备对公共卫生的功能和实用性。这项研究概述了开发人员对健康和健身应用程序的书面描述，并评估了每个应用程序影响行为改变的潜力。本研究的数据来自对 2011 年 2 月 iTunes 上提供的健康和健身应用程序描述的内容分析。健康教育课程分析工具 (HECAT) 和先行-继续模型 (PPM) 被用作框架来指导 3336 个付费应用程序的编码。与成本低于 0.99 美元的应用程序相比，超过 0.99 美元的应用程序更有可能被评分为旨在促进健康或预防疾病（92.55%，1925/3336 vs 83.59%，1411/3336；P<.001），可信或值得信赖（91.11%，1895/3336 vs 86.14%, 1454/3349；P<.001)，更有可能个人使用或推荐给医疗保健客户(72.93%, 1517/2644 vs 66.77%, 1127/2644；P<.001)。与健康饮食、身体活动以及个人健康和保健相关的应用程序比与药物滥用、心理和情绪健康、暴力预防和安全以及性和生殖健康相关的应用程序更常见。强化应用程序不如预置和启用应用程序常见。只有 1.86% (62/3336) 的应用包含所有 3 个因素（即诱发因素、支持因素和强化因素）。开发工作可以针对目前很少有应用程序的公共卫生行为。此外，从业者在推广应用程序的使用时应谨慎，因为它似乎大多数提供与健康相关的信息（诱发）或尝试促成行为，几乎没有一个包含建议行为改变的所有理论因素。
The introduction of Apple’s iPhone provided a platform for developers to design third-party apps, which greatly expanded the functionality and utility of mobile devices for public health. This study provides an overview of the developers’ written descriptions of health and fitness apps and appraises each app’s potential for influencing behavior change. Data for this study came from a content analysis of health and fitness app descriptions available on iTunes during February 2011. The Health Education Curriculum Analysis Tool (HECAT) and the Precede-Proceed Model (PPM) were used as frameworks to guide the coding of 3336 paid apps. Compared to apps with a cost less than US $0.99, apps exceeding US $0.99 were more likely to be scored as intending to promote health or prevent disease (92.55%, 1925/3336 vs 83.59%, 1411/3336; P<.001), to be credible or trustworthy (91.11%, 1895/3336 vs 86.14%, 1454/3349; P<.001), and more likely to be used personally or recommended to a health care client (72.93%, 1517/2644 vs 66.77%, 1127/2644; P<.001). Apps related to healthy eating, physical activity, and personal health and wellness were more common than apps for substance abuse, mental and emotional health, violence prevention and safety, and sexual and reproductive health. Reinforcing apps were less common than predisposing and enabling apps. Only 1.86% (62/3336) of apps included all 3 factors (ie, predisposing, enabling, and reinforcing). Development efforts could target public health behaviors for which few apps currently exist. Furthermore, practitioners should be cautious when promoting the use of apps as it appears most provide health-related information (predisposing) or make attempts at enabling behavior, with almost none including all theoretical factors recommended for behavior change.
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